class Params(object):
    # 数据参数
    _orig_picture_path = "D:/code/pythonCode/PracticeTensorflow/flowers/"    # 原始图片的存储位置
    _classes = {0: 'daisy', 1: 'dandelion', 2: 'rose', 3: 'sunflower', 4: 'tulip'}    # 所有的分类和分类编号
    _num_samples = 4323    # 样本总数
    _num_train = 0
    _num_test = 0
    _samples_path = "D:/code/pythonCode/PracticeTensorflow/data/"    # 数据保存路径
    _logs_train_path = "D:/code/pythonCode/PracticeTensorflow/data/"    # 训练日志保存路径（tensorboard）
    # 训练参数
    _n_classes = 5    # 分类数
    _shape = [64, 64]    # 图片大小
    _batch_size = 100    # 一批数据的数量
    _capacity = 200    # 在队列中的最大元素个数
    _max_step = 20000    # 迭代次数
    _learning_rate = 0.0001    # 学习率

    @property
    def orig_picture_path(self):
        return self._orig_picture_path

    @property
    def classes(self):
        return self._classes

    @property
    def num_samples(self):
        return self._num_samples

    @property
    def num_train(self):
        return self._num_train

    @num_train.setter
    def num_train(self, num):
        self._num_train = num

    @property
    def num_test(self):
        return self._num_test

    @num_test.setter
    def num_test(self, num):
        self._num_test = num

    @property
    def samples_path(self):
        return self._samples_path

    @property
    def n_classes(self):
        return self._n_classes

    @property
    def shape(self):
        return self._shape

    @property
    def batch_size(self):
        return self._batch_size

    @property
    def capacity(self):
        return self._capacity

    @property
    def max_step(self):
        return self._max_step

    @property
    def learning_rate(self):
        return self._learning_rate

    @property
    def logs_train_path(self):
        return self._logs_train_path
